Compiling High Performance Recursive Filters

Abstract : Infinite impulse response (IIR) or recursive filters, are essential for image processing because they turn expensive large-footprint convolutions into operations that have a constant cost per pixel regardless of kernel size. However, their recursive nature constrains the order in which pixels can be computed, severely limiting both parallelism within a filter and memory locality across multiple filters. Prior research has developed algorithms that can compute IIR filters with image tiles. Using a divide-and-recombine strategy inspired by parallel prefix sum, they expose greater parallelism and exploit producer-consumer locality in pipelines of IIR filters over multi-dimensional images. While the principles are simple, it is hard, given a recursive filter, to derive a corresponding tile-parallel algorithm, and even harder to implement and debug it. We show that parallel and locality-aware implementations of IIR filter pipelines can be obtained through {\em program transformations}, which we mechanize through a {\em domain-specific compiler.} We show that the composition of a small set of transformations suffices to cover the space of possible strategies. We also demonstrate that the tiled implementations can be automatically scheduled in hardware-specific manners using a small set of generic heuristics. The programmer specifies the basic recursive filters, and the choice of transformation requires only a few lines of code. Our compiler then generates high-performance implementations that are an order of magnitude faster than standard GPU implementations, and outperform hand tuned tiled implementations of specialized algorithms which require orders of magnitude more programming effort---a few lines of code instead of a few thousand lines per pipeline.
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Communication dans un congrès
High Performance Graphics, Aug 2015, Los Angeles, United States. High Performance Graphics
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Gaurav Chaurasia, Jonathan Ragan-Kelley, Sylvain Paris, George Drettakis, Fredo Durand. Compiling High Performance Recursive Filters. High Performance Graphics, Aug 2015, Los Angeles, United States. High Performance Graphics. 〈hal-01167185〉

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